DocumentCode :
3379949
Title :
Prediction gait during ascending stair by using artificial neural networks
Author :
Prasertsakul, Thunyanoot ; Poonsiri, Jutamanee ; Charoensuk, Warakorn
Author_Institution :
Dept. of Biomed. Eng., Mahidol Univ., Nakornprathom, Thailand
fYear :
2012
fDate :
5-7 Dec. 2012
Firstpage :
1
Lastpage :
5
Abstract :
Walking up or down stairs is an important activity for human lives. Gait pattern of this activity is as same as walking except the range of motion and phase of muscles activities. Many studies have been focused on behavior of this motion. Two cameras and electromyogram (EMG) are the applications used in this study and analysis the motion. To determine the relationship of the both data, it can be performed in many techniques but in this study used artificial neural network model. Nonlinear Autoregressive model with exogenous (NARX) input was applied to this study to define the relationship between the electromyogram of eight muscles and angular displacement of knee and ankle joints of both legs. The results show that the predicted data from NARX were similar to the measured data.
Keywords :
autoregressive processes; bone; cameras; electromyography; gait analysis; medical signal processing; muscle; neural nets; EMG; NARX model; angular displacement; ankle joints; artificial neural networks; cameras; electromyogram; gait pattern; human lives; knee; legs; muscle activities; muscle motion; nonlinear autoregressive-with-exogenous input model; walking; Artificial neural networks; Electromyography; Joints; Knee; Legged locomotion; Muscles; EMG; gait; neural network; nonlinear autoregressive; prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering International Conference (BMEiCON), 2012
Conference_Location :
Ubon Ratchathani
Print_ISBN :
978-1-4673-4890-4
Type :
conf
DOI :
10.1109/BMEiCon.2012.6465464
Filename :
6465464
Link To Document :
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